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We proposed a multichannel deconvolution method. The method uses a mixed norm to promote structured forms of sparsity. To solve this deconvolution problem, we develop a new algorithm called the Hadamard product parametrization (HPP) sparse-group (HPPSG) algorithm. We define each layer of seismic profile as a group, and perform $L_{p}$ -norm for all elements within each group to preserve the lateral continuity. Based on the assumption that the reflectivity is sparse, $L_{q}$ -norm is applied among groups along the time direction. Then, we construct an $L_{p,q}$ optimization problem. After that, we solve this problem using the proposed HPPSG algorithm. The HPPSG algorithm is formed by converting the $L_{p,q}$ optimization function into the $L_{1}$ optimization function which is solved with the help of the HPP algorithm. The proposed algorithm is simple and applicable for an arbitrary $L_{p,q}$ -norm inverse problem. Synthetic and real data examples demonstrate the effectiveness of the proposed method in improving the lateral continuity of seismic profiles.

The application of chemical method for hydrocarbons extraction has attracted increasing interest in the reservoir simulation community. To simulate such reactive transfer processes, compositional flows in porous media with a complex mineralogical must be coupled with the chemical equilibria in the aqueous phase and the precipitation / dissolution reactions of the minerals. The most important time consumed during reactive transport simulation is the geochemical equilibrium (about 30% to 80%). Typically, chemical equilibria are computed for each cell at each time-step by solving an equations system with the iterative Newton-Raphson method. To reduce the computation time, the number of species in solution is often reduce. However, such assumption leads to a less of accuracy of results. Instead of simplifying the geochemical model, an approach that mimic the resolution of geochemical equilibrium can be considered. The aim of the approach is to provide a substitute method to bypass the huge consuming time required to balance the chemical system. This paper focuses on the use of artificial neural networks (ANN) to replace the geochemical equilibrium package. It is widely admitted that ANN are the most efficient response surface model due to the no linear behavior of the output again the parameters. This paper presents a complete workflow for compositional reservoir simulation using an artificial neural network to determine the chemical equilibrium instead of solving equations system. This approach substantially reduces the computation time while keeping an accurate equilibrium calculation. To illustrate the proposed workflow, a case study of CO2 storage in geological formation is presented. The compositional system involves 11 aqueous species, 1 mineral component, 6 chemical equilibrium reactions and 1 mineral dissolution/precipitation reaction.

Our primary investigative tool for understanding the subsurface prospectivity is seismic data, where energy reflected from different seismic horizons can reveal the physical properties of these rocks. The deeper in the earth we look, the weaker the reflected signal will be, so finding ways to boost this signal, without affecting its properties is critical to being able to analyse this signal. Furthermore, seismic interpretation requires a quantitative understanding of the seismic data and it is common practice to assume that the seismic amplitudes can be understood in terms of either acoustic or elastic wave propagation. Preparing ‘interpretation-ready’ seismic data therefore faces two possibly conflicting challenges. On the one hand, seismic processing should conserve the amplitude fidelity of the seismic data. On the other hand, compensation of viscous effects such as attenuation and dispersion facilitates data analysis.

Seismic imaging in the Eastern Siberia region is challenging due to the presence of complex overburden anomalies such as magmatic intrusions and thrusts in the suprasalt complex leading to significant vertical and lateral property variations of high-velocity halite-carbonate geological sections with multiple velocity inversions, complex shallow stratigraphy and substantial topography. Such geological settings create amplitude dimming and wipeouts in the images and cause structural distortions at the reservoir level. We applied full-waveform inversion (FWI) technology to overcome limitations of the conventional workflow and to support the exploration programme. The primary output of FWI is a high-resolution subsurface velocity model, which can be used as an attribute to improve interpretation of the overburden sediments, to identify shallow hazards, to derisk exploration prospects and to optimize well placement. We tested FWI on a conventional 3D land data set to create a near-surface velocity model. Detailed subsurface models generated with FWI provided an accurate description of the overburden and helped us to investigate shallow geological environments. Predrill predictions using the FWI velocity volume showed excellent agreement with well measurements and made it possible to recommend the technology for inclusion in the processing flow.

A seismic survey was conducted in a production oilfield located in Serbia, confined to the Pre-Neogene (Paleozoic) base of the Pannonian basin. It was assumed that additional significant unrecovered residual reserves still exist in this oil field, as well as additional similar undiscovered reservoirs. The further characterization of the existing reservoirs, and the identification and characterization of the new ones, required the implementation of advanced seismic imaging technology. Hence, a new project was designed composed of the following steps: Obtaining the highest possible seismic resolution in the area, and creating an updated, high-definition subsurface model that includes the structural complexities of the geological layers and the azimuthal anisotropic effects (e.g., fracture systems), especially within the target layers. This enables the identification and characterization of the target productive zones, making it possible to accurately design and plan the well placement. A modern, full-azimuth seismic survey was performed with a fairly regular distribution of the source-receiver offsets and azimuths. The dominant fold (number of traces per shot) was about 120. The seismic sources consisted of groups of vibrators with a linear sweep signal, where the frequency range was 6 to 96 Hz and the time duration 15 seconds. Emerson’s EarthStudy 360 full-azimuth angle domain imaging system (Koren and Ravve, 2011) was chosen to facilitate the above-mentioned tasks. This is an advanced subsurface imaging system operating directly in the Local Angle Domain (LAD). The high-resolution images with the unique full-azimuth directional and reflection angle common image gathers obtained by this seismic migration technology make it possible to better define the structural subsurface model and furthermore, to detect fine interlayer fracture systems at the target areas. Both regional faults and low-amplitude sub-seismic faults (fracture indicators at these regions) were mapped. The main imaging characteristics were correlated with existing production wells in the area

In recent years, joint inversion has been widely used for integrated geological interpretation. We extended a data-space joint inversion algorithm of magnetotelluric, gravity and magnetic data to include first-arrival seismic travel-time and normalized cross-gradient constraints. We describe the main features of the algorithm and apply it to synthetic data generated for hypothetical models. For the synthetic data, we find that the joint inversion with multiple parameters is superior to the joint inversion with two or even three parameters, which can reduce the multisolution of inversion results more effectively. Furthermore, data-space joint inversion involves fewer memory requirements and better calculation speeds than traditional model-space joint inversion. The normalized cross-gradient constraints can better couple model parameters of different magnitudes compared with traditional unnormalized cross-gradient constraints, resulting in higher levels of structural similarity among resistivity, density, magnetic susceptibility and velocity models.

Key minerals may soon be in short supply as shallow mineral deposits are mined-out; therefore exploration for economically feasible deep-seated deposits to sustain a long-term global growth is a great challenge. New deposits are likely to be found using reflection seismic surveys in combination with drilling, field geological mapping and other geophysical methods. Seismic methods have already have contributed significantly to the discovery of some of the world’s major mineral deposits (Milkereit et al., 1996; Pretorius et al., 2000; Trickett et al., 2004; Malehmir and Bellefleur, 2009; Malehmir et al., 2012). However, use of the method is not widespread because it is deemed to be expensive. Although improvements in computing capabilities have led to cost reductions, the costs are still beyond exploration budgets of many companies. Thus, mining companies have had little financial ability to acquire new reflection seismic data, and very little governmental support has been available to acquire research seismic surveys for mineral exploration. Over the last few years, there has been a proliferation of seismic solutions that employ various combinations of equip-ment, acquisition, and processing techniques, which can be applied in hard rock situations to improve the imaging resolution (Denis et al., 2013). The best acquisition solutions to date have come from the deployment of high-density receiver and source arrays which the extension of the seismic bandwidth to six octaves using broadband sources (Duval, 2012). Another area of seismic research has focused on surface seismic acquisition using three-component (3C) microelectro-mechanical (MEMS-based) seismic landstreamers (Brodic et al., 2015), coupled with wireless seismic recorders, and surface-tunnel-seismic surveys (Brodic et al., 2017). However, numerous difficulties have been encountered, even with these innovative acquisition seismic approaches. Seismic surveys acquired in the mining regions suffer from noise produced by the drilling, blasting and transport of rock and the crushing of ore. Furthermore, in some mining regions the acquisition of new data is not permitted due to new environmental regulations. In such a fast evolving seismic technological era, legacy reflection seismic data are often regarded by mining companies and geoscientists as inferior compared with the newly acquired data. This paper demonstrates that if the legacy data are properly retrieved, reprocessed, and interpreted using today’s standard techniques, they can be of significant value, particularly in the mining regions where no other data are available or the acqui-sition of new data is difficult and expensive. The development of multitudes of processing algorithms and seismic attributes, in particular, make it worthwhile to reprocess and interpret legacy data to enhance the detection of steeply dipping structures and geological features below the conventional seismic resolution limits (i.e., a quarter of the dominant wavelength), which was not possible with the tools that were available when the data were originally acquired and processed. The new information obtained from the legacy data may benefit future mine planning operations by discovering new ore deposits, providing a better estimation of the resources and information that will help to site and sink future shafts. Thus, any future mineral exploration project could also take the geological information obtained from the reprocessed and interpreted legacy seismic data into account when planning new advanced seismic surveys (Manzi et al., 2018). The latest seismic algorithms are particularly interesting to South Africa’s deep mining industry because South Africa has the world’s largest hard rock seismic database, which could benefit from new processing techniques and attributes analyses. These techniques could be applied to legacy seismic data to identify areas of interest, improve structural resolution and to locate deeper ore deposits. Seismic attributes, in particular, could be used to identify any subtle geological structures crosscutting these deposits ahead of the mining face that could affect mine planning and safety.

The benefits of working with legacy seismic data are broad and valued in a wide range of geoscience applications and result from the comprehensive volume of industry and public seismic data acquired over several decades. Legacy seismic data exist in many parts of the world including areas that, due to stricter regulatory processes, environmental restrictions, demographic changes, or other factors would be challenging or even impossible to survey today. Examples are numerous but one includes 2D marine seismic data acquired in the 1980s with a large airgun array to provide a deep cross-section through the Appalachians beneath the now sen-sitive Gulf of St Lawrence, eastern Canada (Marillier et al., 1989). Sometimes benefits arise through the use of newly developed tech-niques to extract additional information from legacy seismic data. This idea is obviously not new and many examples can be found in the literature. One example is the use of extended Vibroseis cor-relation developed in 1980s (Okaya and Jarchow, 1989) applied to increase the depth range of marine Vibroseis seismic data acquired in 1971 in two of the Great Lakes of North America (Milkereit et al., 1992). Marine seismic data in the Great Lakes are sparse, but contain information about deep Grenvillian terranes that, in this case, could only be revealed using a technology developed more than a decade after data acquisition. Reflection seismology has been used for mineral exploration for more than 30 years (Reed, 1993). During that period, many case studies demonstrated the utility of the method for imaging deep lithological contacts and structures indirectly associated with mineralization, and for the direct imaging of deposits. Malehmir et al. (2012) provide a comprehensive overview of key accomplishments for various commodities and mining locations in Canada and around the world. In particular, many examples demonstrate the advantages of the 3D seismic method for providing high-resolution images of subsurface structures and deep-seated ore deposits in a variety of geological environ-ments. Several of these legacy 3D seismic data sets have been reprocessed with advanced and novel techniques to provide more reliable and detailed images of the subsurface. Here, we show three early examples of the application of 3D seismic data for mineral exploration in the Bathurst, Sudbury, and Val d’Or mining camps, Canada (Figure 1). Specifically, we demonstrate that reprocessing of 3D datasets from earlier applications of seismic reflection can refine the imaging of known ore deposits and can lead to the identification of new exploration targets. For the case studies presented here, most improvements resulted from processing and imaging strategies built from an understanding of the response of mineralized bodies on seismic data and improving specific steps that prevented their proper imaging on final volumes. The case studies are introduced according to their year of acquisition, starting from the oldest (i.e., the Trill 3D survey in the Sudbury mining camp) to the most recent (e.g., the Louvicourt 3D survey in the Val d’Or mining camp). All 3D seismic surveys are located in areas with limited access and difficult terrain and as a result, were acquired with explosives. Surface conditions varied for each survey area but included steep hills, extensive swamps, and thick glacial sediments. Geology also varied at the three sites. Host rocks are either nearly-transparent-to-seismic waves or are highly heterogeneous and generating seismic scattering potentially masking the response of the mineralized body. In all three areas, however, mineralized bodies scattered or reflected energy in a preferred direction, and were observed only on a limited number of prestack seismic traces. In some cases, such a sparse signature was buried in noise when stacking all traces and required particu-lar attention to be properly imaged.

Unresolved velocity anomalies lead to distortion in images: consequently, much effort has gone into developing model-building techniques to identify such anomalies. Historically, the industry has relied on ray-based tomography to achieve this, but ray methods are limited to detecting features that are typically larger than about five times the dominant wavelength of the recorded seismic data. More recently, model building based on wavefield tomography has been introduced (full waveform inversion). Waveform inversion methods are more costly than ray methods, but have the potential to resolve features smaller than the recorded seismic wavelengths. Using waveform inversion to update a parameter field comprises two main steps: firstly, determine the spatial location of where an observed error came from, and then, determine the magnitude of that error, so as to update the parameter model. The first step uses the same principles as reverse-time migration to construct an ‘image’ of the parameter error, and the second step employs gradient descent methods to estimate the magnitude of the required parameter update. In this tutorial, I will describe both steps of the waveform inversion procedure, and also discuss differing methods of characterizing the error in a given parameter model.

Blended or simultaneous source shooting is becoming more widely used in seismic exploration and monitoring, which can provide significant uplift in terms of acquisition quality and economic efficiency. Effective deblending techniques are essential to make use of existing processing and imaging methodologies. When dealing with coarse and/or irregularly sampled blended data, the aliasing noise of incomplete data will affect the deblending process and the crosstalk in the blended data will also have a negative influence on the process of data reconstruction. Thus, we have developed a joint deblending and data-reconstruction method using the double-focal transformation to eliminate blending noise and aliasing noise in the coarse, blended data. Numerically blended synthetic and field-data examples demonstrate the validity of its application for deblending and data reconstruction. We also investigate the effect of random noise on the recovery process, and it shows that the algorithm would obtain optimum results after applying a denoising process before deblending and data reconstruction.

The interpretation of fault surfaces is key to understanding the subsurface geology represented in 3D seismic volumes. The geologic structure represented by seismic reflections can be auto-tracked in the volume. Faults, however, are imaged as discontinuities or changes in curvature in the seismic data. For many years, fault interpretation involved manually picking fault cuts on orthogonal slices through the seismic volume. These fault cuts were grouped into conceptual faults, and 3D fault surfaces were created from the fault cuts. In the 1990s, the development of attributes to highlight discontinuities in 3D seismic data was pervasive in the industry. Perhaps the most well known of these efforts was the development of Coherence (Bahorich and Farmer, 1995; Gersztenkorn and Marfurt, 1996; Marfurt, et al., 1999). Although coherence or edge attributes highlighted faults in the seismic volume, the fault imaging was insufficient to support automatic extraction of the fault surfaces. These attributes provided guidance to the manual interpretation of faults in the 3D volumes. This paper describes a portion of the history behind the development of techniques to improve 3D fault imaging to the point where fault surfaces can be automatically extracted from seismic volumes. A windowed Radon transform-based technique is then described and applied to the F3 survey from the North Sea. This technique produces fault images that are of sufficient quality to support automatic extraction.

Low-frequency seismic anomalies have long been a subject of interest to geoscientists involved in hydrocarbon exploration since such ‘gas-shadows’ can be a direct hydrocarbon indicator (DHI). Published studies have demonstrated evidence for them potentially resulting from increased seismic attenuation and velocity dispersion, as a result of hydrocarbon saturation. The topic gained wide interest during the 2000s with well-cited publications by Castagna et al. (2003), Ebrom (2004), Chapman et al. (2005, 2006) and Odebeatu et al. (2006), to name a few. The consensus of these studies was that hydrocarbon related frequency effects are predicted to be detectable on stacked seismic data. Furthermore, it has been suggested that low frequencies tend to show the highest sensitivity to fluid changes. (e.g. Korneev et al., 2004). The effect has been shown not only from seismic data; studies involving laboratory tests and borehole data provide similar conclusions. Overall there is general agreement that the effect exists. However the physical cause remains inconclusive. Several studies have also shown evidence that hydrocarbon reservoirs have an amplitude-versus-offset (AVO) frequency dependence (e.g. Chapman et al. (2005, 2006), Odebeatu et al. (2006), Liu et al. (2006), Ren et al. (2007), Zhang et al. (2007), Chen et al. (2008), Wu et al. (2014)). In the modelled case of gas-saturated sands, low frequencies have tended to show the greatest change in amplitude with offset (Figure 1a). The idea of using AVO and Spectral Decomposition (SD) to understand frequency anomalies and potential links to reservoir fluid content has been approached by several of these authors. The published work largely used model-based techniques to predict AVO effects for different frequencies (Figure 1b), and then applied this information to aid interpretation of anomalies observed on iso-frequencies sections. The results convincingly suggest that there are differences in the spectral content of seismic data which could be exploited for improved hydrocarbon identification. The results of these pioneering publications is the basis from which the workflow presented in this paper was conceived. Here these ideas are approached from an interpretation perspective and applied in a practical manner using commercial interpretation software.

The presence of geophysical receivers on the seafloor changes the local wave field due to the receiver seafloor interaction. The resulting PP‐ and PS‐wave distortion of the wave field is often referred to as receiver coupling to the seafloor and can make data processing challenging and sometimes impossible. This paper provides an overview of the mathematical approaches to describe receiver coupling, how to estimate receiver coupling and what the difficulties and possible solutions are. The first section shows how the mathematical approach developed from a simple model considering only the vertical receiver component to include all three receiver components and their interactions with the seafloor. In the second section, I show how receiver coupling can be measured and how it can be improved using mathematical and data‐driven approaches.

Occidental Petroleum Corporation’s (Oxy’s) US business is focused on the Permian Basin of West Texas and Southeast New Mexico. With nearly 2.5 million net acres, Oxy produces hydrocarbons from every producible formation in the Permian Basin. To efficiently unlock value from this extensive acreage and operating position, Oxy has developed an unconventional resource play appraisal and development workflow within which geophysics plays an integral role. This is notable given that just a couple of years ago geophysical data and analysis played a very minor role in our industry’s unconventional resource play business decision-making process in this basin. Our Permian Basin appraisal and development workflow starts with a regional basin overview to identify the most likely rich source rocks and production analogs. We then develop an understanding of the geochemistry of the source rocks by means of cuttings and core analyses. Next, individual benches are appraised using pilot holes and state-of-the-art 3D pre-stack seismic data, conditioned in-house to meet the requirements for quantitative interpretation. All available data are integrated through multi-disciplinary studies to yield a thorough understanding of the petrophysical, geophysical, and geomechanical properties that impact well performance. Pre-stack depth-migrated 3D seismic attributes, including estimated pore-pressure and geomechanical flow units, are used extensively for planning the well’s landing zone and trajectory, and also during operations to steer the well through the target zone. Microseismic data are used with tracer and pressure data to confirm our hydraulic fracture models. Recently, production data have confirmed the value of our interpreted seismic attributes, confirming the guidance that interpreted seismic data need to be an integral part of new well planning in the basin.

Reservoir monitoring is required in understanding reservoir behaviour under dynamic conditions associated with enhanced oil recovery processes related to carbon dioxide injection and shale reservoir development through multistage hydraulic fracturing. Geochemical and geomechanical changes associated with these processes may affect reservoir permeability both positively and negatively. These changes need to be monitored to understand the causative mechanism of these changes and to mitigate potential harmful effects including damage to our reservoirs. Completion and production processes cause dynamic changes in reservoir properties. The most accurate geophysical tool for monitoring these changes is time-lapse, multi-component seismology, specifically enabling the use of shear wave azimuthal anisotropy for reservoir monitoring of effective stresses in the reservoir. Studies over the past 23 years by the Reservoir Characterization Project (RCP) document the power of shear wave azimuthal anisotropy to observe and quantify stress changes in our reservoirs. Our studies focus on carbonate and clastic rocks where changes in rigidity, detected using measurements of shear wave azimuthal anisotropy, are the primary observations to infer reservoir processes. All projects are full waveform data volumes utilizing both vertical and horizontal vibrators as P- and S-wave sources recorded by multi-component geophones. This paper portrays results of time-lapse, multi-component studies at Vacuum, Weyburn, and Wattenberg Fields conducted by the Reservoir Characterization Project. Both Vacuum and Weyburn Fields are carbonate reservoirs undergoing tertiary recovery using CO2 injection. Wattenberg Field is a mixed carbonate/shale reservoir undergoing horizontal drilling and multistage hydraulic fracturing. Results show that stress changes associated with the reservoir processes involving enhanced oil recovery and hydraulic fracturing result in shear wave azimuthal anisotropy changes detected using time-lapse, multi-component seismic data.

Time-Lapse (4D) seismic data has shown to be a successful tool in monitoring a field and its production using two or more 3D seismic cubes spaced by months or by years. At the end of the 4D processing, two seismic cubes, named Base and Monitor, are obtained using a similar processing sequence. Each cube represents the snapshot of the reservoir at a given time. It allows a better understanding of the field, thus supporting operations. Prior to processing the data, a complete study was done to analyse the likelihood of seeing a 4D difference despite two different acquisition layouts. Throughout a complete processing in both time and depth domains, 4D attributes are being analysed over the field giving confidence in the quality of the dataset. Finally, a full 4D analysis helps us to develop a better understanding of the field fluid transfer mechanism allowing improved optimization the field.

Time-lapse seismic monitoring is one of the critical technologies providing the active exploration of hydrocarbon deposits. In desert environments, many challenges are complicating its practical application. The paper deals with one of them – changes of topography due to a mobility of the sands. To assess this impact on the predictability, which is the measure of repeatability computed as cross-correlation of traces, the full numerical simulation is done. The primary attention is paid to the early arrivals because they are most sensitive to the change of a near-surface structure. This perturbation leads to the so-called “non-repeatable” noise which is one of the main trouble in time-lapse seismic monitoring. A standard measure to characterize a non-repeatable noise is to consider the energy of the difference if two data sets/images and compare it with the energy of each data/image. This value is known as the NRMS. If there is a perfect repeatability NRMS = 0, for random uncorrelated noise NRMS = 141%, and if the data sets are identical but polarity-reversed NRMS = 200%. In the paper, we demonstrate that for a homogeneous subsurface layer repeatability depends mainly on changes of the surface topography but not of its slope. At the same time, if one deals with a heterogeneous near-surface, repeatability is far worse for the zones with a thin sand layer (less than 5 m). There can happen significant non-repeatability with NRMS error greater than 60% and reduction of predictability below 75%. These values are similar to the NRMS measured on field data in Saudi Arabia, suggesting that such factors may be significant for land 4D seismic in a desert. Also, sand topography variations can be accumulated thus explaining experimentally observed trends showing that land seismic repeatability degrades over time from days to months and years.

Applications of full-waveform inversion (FWI) to land seismic data exhibit specific challenges, largely associated with elastic effects and near-surface heterogeneities. This explains why only a few land FWI case studies have been published to date (Mothi et al., 2012; Mei et al., 2014). In recent years, the acquisition design of land surveys has improved dramatically and now offers ideal conditions for FWI: dense sampling, long offsets and full azimuths (FAZ), and very low frequencies down to 1.5 Hz (Mahrooqi et al., 2012). The first published application of 3D land FWI to this new, ultra-low frequency, data set was encouraging (Stopin et al., 2014). The authors demonstrated the capability to recover the long spatial wavelength components of the velocity model, robustly and efficiently, using diving wave FWI and basic data pre-processing. It was proposed that the resulting velocity model be used as a starting model for reflection-based tomography. Limitations in obtaining a high-resolution velocity model (> 6 Hz) from FWI were identified, and attributed to the acoustic assumption and a weak signal-to-noise ratio.

Recent step changes in seismic processing and imaging technology have delivered dramatic improvements in resolution, velocity model building and multiple attenuation. This article will explore improvements in resolution that have been demonstrated on two multi-client surveys in the North Sea: Cornerstone and Northern Viking Graben (NVG). Extending full-waveform inversion (FWI) to include absorption effects as well as velocity has delivered improved imaging, higher resolution and more reliable AVO products for the NVG survey, and this will now be applied to the reprocessed Cornerstone data. Both surveys cover more than 35,000 km2 each, so application of high-resolution processing sequences to these two data sets will deliver advanced high-resolution data over two large areas of the North Sea. The NVG survey was acquired using BroadSeis variable-depth streamers in conjunction with a broadband source to maximize the bandwidth. However, new developments in broadband processing, including ghost wavefield elimination (GWE) and bandwidth extension, can be extended to the reprocessing of conventionally-acquired data sets, which can now be uplifted to deliver data of almost similar quality to modern broadband data by mitigating many of the limitations of traditional acquisition. This is demonstrated by the reprocessing of the Cornerstone project in the Central North Sea. Although this survey was recently reprocessed in depth using multi-layer tomography, the rapid improvements in GWE, multiple and noise attenuation, velocity modelling and imaging in the last few years mean that it can still benefit from being reprocessed again. Modern processing techniques ensure compliance with amplitude versus offset (AVO) analysis, and AVO attributes are used for QC purposes during the processing flow to ensure that the final data sets can be used directly for reservoir characterization. The AVO attribute maps for Cornerstone shown later in this article have already delivered impressive high-resolution images of the Forties field

We present an integrated geological and geophysical study conducted during the acquisition and processing of extensive 3D Multi-Client seismic campaigns offshore Gabon. These campaigns resulted in two distinct surveys, the first of 11.500 km2 in the southern shelf, and a second of 5500 km2 to the north, offshore Libreville (Figure 1). The acquisition parameters and survey design were planned with seismic illumination studies, long offset streamers were utilised and the data was processed with a modern broadband sequence (Esestime et al., 2017). The surveys presented various imaging challenges, from shallow water multiples to shallow high velocities, carbonate and salt. The Gabonese Authorities for Hydrocarbon (DGH) provided a comprehensive well dataset, including geological markers, logs and checkshot data. These penetrated both pre-salt and post-salt sections, and provided valuable data during all stages of the velocity model building, especially for the southern part of the area. Well data was more limited for the northern survey, where previous exploration stopped mainly in the post-salt shallow section and velocity logs are limited to a few wells. The continuous iteration of geological information at every stage of the processing allowed an integration of the geological information at multiple stages. In particular, pre-stack and poststackanalyses allowed for determining regional petro-physical properties, such as ‘recurrent velocity trends’ which are useful to interpret at multiple scales from post-stack to single gather data. We obtained accurate seismic velocities, regionally consistent with the geology from sparse wells. Excellent seismic-to-well tie was achieved on the final depth data in South Gabon, from wells 50-70 km apart, in a highly variable structural stratigraphic setting, dominated by tectonics and salt movement. The results provided a strong learning curve for analysis and QC of several intermediate velocity models obtained from the tomographic updates during the depth migration exercises (Kirchhoff PreSDM).

During the time taken for seismic data to be acquired, reservoir pressure may fluctuate as a consequence of field production and operational procedures and fluid fronts may move significantly. These variations prevent accurate quantitative measurement of the reservoir change using 4D seismic data. Modelling studies on the Norne field simulation model using acquisition data from ocean-bottom seismometer and towed streamer systems indicate that the pre-stack intra-survey reservoir fluctuations are important and cannot be neglected. Similarly, the time-lapse seismic image in the post-stack domain does not represent a difference between two states of the reservoir at a unique base and monitor time, but is a mixed version of reality that depends on the sequence and timing of seismic shooting. The outcome is a lack of accuracy in the measurement of reservoir changes using the resulting processed and stacked 4D seismic data. Even for perfect spatial repeatability between surveys, a spatially variant noise floor is still anticipated to remain. For our particular North Sea acquisition data, we find that towed streamer data are more affected than the ocean-bottom seismometer data. We think that this may be typical for towed streamers due to their restricted aperture compared to ocean-bottom seismometer acquisitions, even for a favourable time sequence of shooting and spatial repeatability. Importantly, the pressure signals on the near and far offset stacks commonly used in quantitative 4D seismic inversion are found to be inconsistent due to the acquisition timestamp. Saturation changes at the boundaries of fluid fronts appear to show a similar inconsistency across sub-stacks. We recommend that 4D data are shot in a consistent manner to optimize aerial time coverage, and that additionally, the timestamp of the acquisition should be used to optimize pre-stack quantitative reservoir analysis.

Measurement of dispersed vitrinite reflectance in organic sediments is one of the few regional data sets used for placing bounds on the thermal history of a sedimentary basin. Reflectance data are important when access to complementary information such as high‐quality seismic data is unavailable to place bounds on subsidence history and in locations where uplift is an important part of the basin history. Attributes which make vitrinite reflectance measurements a useful data set are the relative ease of making the measurement, and the availability of archived well cores and cuttings in state, provincial, and federal facilities. In order to fully utilize vitrinite data for estimating the temperature history in a basin, physically based methods are required to calibrate an equivalent reflectance from a modelled temperature history with measured data. The most common method for calculating a numerical vitrinite reflectance from temperature history is the EASY%Ro method which we show systematically underestimates measured data. We present a new calculated reflectance model and an adjustment to EASY%Ro which makes the correlation between measured vitrinite values and calculated vitrinite values a physical relationship and more useful for constraining thermal models. We then show that calibrating the thermal history to vitrinite on a constant age date surface (e.g., top Cretaceous) instead of calibrating the thermal history in depth removes the heating rate component from the reflectance calculation and makes thermal history calibration easier to understand and more directly related to heat flow. Finally, we use bounds on the vitrinite–temperature relationships on a constant age date surface to show that significant uncertainty exists in the vitrinite data reported in most data sets.

Up–down wavefield decomposition is effectuated by a scaled addition or subtraction of the pressure and vertical particle velocity, generally on horizontal or vertical surfaces, and works well for data given on such surfaces. The method, however, is not applicable to decomposing a wavefield when it is given at one instance in time, i.e. on snapshots. Such situations occur when a wavefield is modelled with methods like finite-difference techniques, for the purpose of, for example, reverse time migration, where the entire wavefield is determined per time instance. We present an alternative decomposition method that is exact when working on snapshots of an acoustic wavefield in a homogeneous medium, but can easily be approximated to heterogeneous media, and allows the wavefield to be decomposed in arbitrary directions. Such a directional snapshot wavefield decomposition is achieved by recasting the acoustic system in terms of the time derivative of the pressure and the vertical particle velocity, as opposed to the vertical derivative in up–down decomposition for data given on a horizontal surface. As in up–down decomposition of data given at a horizontal surface, the system can be eigenvalue decomposed and the inverse of the eigenvector matrix decomposes the wavefield snapshot into fields of opposite directions, including up–down decomposition. As the vertical particle velocity can be rotated at will, this allows for decomposition of the wavefield into any spatial direction; even spatially varying directions are possible. We show the power and effectiveness of the method by synthetic examples and models of increasing complexity.

The estimation of hydraulic parameters is critical for the rational use of water resources and the development of reliable hydrogeological models. However, the cost of such estimation can be very high and the data are limited to the area near the pumping well. For this reason, complementary methods for estimating hydraulic conductivity and transmissivity have become increasingly important in recent years, such as the adjustment of empirical relationships between geoelectrical and hydraulic parameters. In this paper, two linear relationships were tested, combining resistivity measurements from well logging profiles and hydraulic conductivity values from pumping test data, in a semi-confined fluvial aquifer in the province of Buenos Aires, Argentina. Furthermore, these relationships were used to obtain two-dimensional (2D) hydraulic conductivity and transmissivity sections from electrical resistivity tomography using a high-definition electrode array. Predicted values were compared with traditional pumping test in a near well showing very good agreement with both methods. Results showed that it would be possible to quantify the 2D variation of hydraulic parameters in aquifers and to identify high- or low-productivity areas. By knowing this information in advance, it is possible to reduce the number of failures or unexpected results when drilling a well. These 2D sections also provide additional information about hydraulic parameters and their lateral variability, and can improve hydrogeological models without drilling new wells. Fil: Perdomo, Santiago. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia del Noroeste de la Provincia de Buenos Aires. Universidad Nacional del Noroeste de la Provincia de Buenos Aires. Centro de Investigaciones y Transferencia del Noroeste de la Provincia de Buenos Aires; Argentina Fil: Kruse, Eduardo Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina. Facultad de Ciencias Naturales y Museo, Universidad Nacional de la Plata; Argentina Fil: Ainchil, Jeronimo Enrique. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina

Imaging through a heterogeneous shallow gas-charged overburden, such as a gas cloud, presents several imaging challenges and is a demanding problem to solve. Our preferred technical solution for imaging beneath gas clouds is to utilize converted wave imaging (Radzi et al., 2015), but this is not always available or cost effective and velocity model building is still difficult. Many previous case studies have been produced from Malaysia which demonstrate subsurface imaging techniques and improvements for fields affected by gas clouds, e.g., Akalin et al. (2010); El Kady et al. (2012); Abd Rahim et al. (2013); Ghazali et al. (2016) and Gudipati et al. (2018). In this paper, we describe a new comprehensive high-density experimental project to readdress these ever-challenging seismic issues by imaging the reservoir from both above and within existing boreholes. The integration of multiple technologies has significantly improved the subsurface images of the field including better-quality velocity models below gas clouds. The new data reveal a larger scale of near-surface heterogeneities than previously expected and future studies will selectively reprocess subsets of the acquired data in order to optimize the images; and, by extension to other similar fields, address a cost-effective imaging strategy.

Broadband towed-streamer data has extended the usable seismic bandwidth at both ends of the frequency spectrum. As well as enriching the overall seismic image, improved low frequencies have delivered more reliable full-waveform inversion results and more quantitative elastic inversion, while improved high frequencies enable better interpretation of thin-layered structures. Various strategies have been developed to acquire broadband data, ranging from processing-only approaches using horizontal-tow hydrophone-only streamers, to combined acquisition and processing schemes using multi-level streamers (Posthumus, 1993), variable-depth streamers (Soubaras, 2010) or multi-sensor streamers (Carlson et al., 2007). The desire to extend all the benefits of broadband 3D data to 4D time-lapse surveys has been constrained by the requirement for repeatability between successive surveys. The use of deeptowed multi-sensor streamers in time-lapse acquisition creates challenges, as the existing baseline surveys will often have been acquired using a shallow-tow streamer. For optimal 4D repeatability, subsequent monitor acquisitions would traditionally be acquired using the same streamer depth as the earlier surveys. Using a case study from the North Sea, we tested recording monitor data at a deeper streamer depth than the baseline survey using multi-sensor streamers, and then redatuming to simulate data recorded at the shallow streamer depth. Based on the successful outcome of this trial, we successfully acquired two 4D monitor surveys during the recent summer season using this method.

Traditional exploration and prospecting for hydrocarbons (HC) has traditionally been carried out using seismic techniques. At the same time, it is well known that seismic techniques are inefficient in the presence of high-velocity layers (which reduce resolution at great depth), igneous rocks, thrusts within the crystalline basement, and tight limestone. Being sensitive to geological structure, seismic techniques are characterized by low resolution at the level of micro-parameters such as fluid type, porosity/ fracture, and degree of pores HC-saturation. Moreover, technical complications, e.g., highly rugged topography, dense vegetation and object remoteness may make seismic surveys difficult, expensive, or even impossible. Therefore, non-seismic methods are increasingly used in HC exploration and prospecting. In particular, electrical and electromagnetic (EM) methods (magnetotelluric sounding, direct current, time-domain EM (TDEM), induced polarization (IP), controlled source EM, etc.) complement seismic techniques and increasingly replace them (Johansen, 2008; Key, 2012; Zhang et al., 2014; Barsukov and Fainberg, 2015; Berdichevsky et al., 2015, among others). In parallel with EM, the efficient technologies for 3D modelling and inversion (see, for instance, a review paper by Siripunvaraporn (2012) and references therein) and integrated analysis of EM and other geophysical data (see, for instance, a review paper by Bedrosian (2007) has been created. Application of these methods in solving problems of exploration geophysics enabled progression in exploration, prospecting, and devel¬opment of HC deposits (see, for instance, a review paper by Strack (2014) and references therein). Meanwhile, very recent advances in indirect estimating of rock geophysical properties of lithologic reservoirs from electromagnetic sounding data (Spichak and Goidina, 2016; Spichak and Zakharova, 2015, 2016; Spichak, 2017) open up new possibilities related to development of more sophisticated approaches to estimation of the reservoir properties and its potential assessment. The purpose of this paper is to demonstrate the advanced capabilities of electromagnetic techniques in solving a wide range of prob-lems, especially those which seismic surveys are not effective in solving.

Since the early discovery of a black-smoker complex in 1978 on the East Pacific Rise at 21°N, speculations and expectations have been driven about the potential and perspectives of mining seafloor massive sulfide (SMS) deposits in the deep-ocean. With a worldwide accelerating industrialization, emerging markets, increased commodity prices and metal demand, and advance¬ments in deep-water mining and extraction technologies, mining of SMS may become economically feasible in the near future (Kowalczyk, 2008). However, we still know little about the resource potential of SMS deposits, and the development of geophysical methods for an assessment of their spatial extent, composition, and inner structure is crucial to derive a proper assessment of their economic value. Novel geophysical mapping techniques and exploration strategies are required to locate extinct and buried clusters of SMS deposits, away from the active vent fields and of larger economic potential, but are difficult to find and sample by conventional methods. In 2015 the International Seabed Authority (ISA) assigned an exploration license for polymetallic sulfide deposits to the German Federal Institute for Geosciences and Natural Resources (BGR) in a specified area comprising 100 patches, each 10 . 10 km in size, distributed along the Central and Southeastern Indian Ridge. The challenge to acquire high resolution near-surface electromagnetic (EM) data in such geologically and morphologically complex mid-ocean ridge environments has been addressed by our recent development of the deep-sea profiler Golden Eye that utilizes a frequency-domain electromagnetic (FDEM) central loop sensor, of 3.3 m diameter (Muller et al., 2016). This system has been used in 2015 and 2017 to map active and relict hydrothermal vent fields in the SMS licensing areas. Aside from technological developments, this paper discusses new data processing routines and methods to unravel the conductivity-depth-distribution, induced polarization and magnetic susceptibility, and joint interpretation with geochem¬istry as key elements to map and evaluate SMS deposits.

Since the late 1990s, the continuous development and application of the Controlled-Source Electromagnetic (CSEM) technology have vastly improved its usage in exploration (e.g., Constable, 2010; Loseth et al., 2015; Zach et al., 2009). CSEM inversion results are the main input for interpretation of resistivity data, especially potential fluid anomalies. Complementary to other geophysical methods, e.g. Amplitude versus Offset (AVO), it can therefore be a valuable tool in hydrocarbon exploration. Yet, the unconstrained nature of the subsurface and non-unique¬ness of inversions is a tough predicament. For example, several features in the subsurface could cause high resistivity, such as abundant limestone, salt, basalt, mature source rocks or hydro¬carbon-filled sandstones (Baltar and Barker, 2015). As a result of enhanced data quality, data processing and inversion capabilities, together with improved workflows and accumulated experience, CSEM interpretation has become increasingly more robust (Buland et al., 2011; Karman et al., 2013; Loseth et al., 2014). The 3D Gauss-Newton (GN) inversion algorithm is a more robust method compared to other inversion types. GN thus provides a new, powerful methodology for generating marine CSEM resistivity images. Nonetheless, it has formerly been com¬putationally exhaustive to apply. With the Hoop area, Barents Sea, recently being nominated for the Barents Sea exploration licensing round, a tight deadline was given for the CSEM inversion of an expansive 11,000 km2, over 130 blocks (refer to Figure 1). Adopt¬ing the flexible and agile cloud system into the CSEM workflow, it has improved the 3D GN work efficiency and provided overall consistent results when compared with other CSEM inversion schemes. This paper will illustrate how a systemic workflow of CSEM 3D GN inversions together with efficient cloud computing, could lead to a more consistent interpretation of this data.

Obtaining an accurate image of the subsurface still remains a great challenge for the seismic method. Migration algorithms aim mainly on positioning seismic events in complex geological contexts. Multiple reflections are typically not accounted for in this process, which can lead to the emergence of artefacts. In Marchenko imaging, we retrieve the complete up- and downgoing wavefields in the subsurface to construct an image without such artefacts. The quality of this image depends on the type of imaging condition that is applied. In this paper, we propose an imaging condition that is based on stabilized unidimensional deconvolution. This condition is computationally much cheaper than multidimensional deconvolution, which has been proposed for Marchenko imaging earlier. Two specific approaches are considered. In the first approach, we use the full up- and downgoing wavefields for deconvolution. Although this leads to balanced and relatively accurate amplitudes, the crosstalk is not completely removed. The second approach is to incorporate the initial focussing function in the deconvolution process, in such a way that the retrieval of crosstalk is avoided. We compare images with the results of the classical cross-correlation imaging condition, which we apply to reverse-time migrated wavefields and to the up- and downgoing wavefields that are retrieved by the Marchenko method.

Seismic time-lapse surveys are susceptible to repeatability errors due to varying environmental conditions. To mitigate this problem, we propose the use of interferometric least-squares migration to estimate the migration images for the baseline and monitor surveys. Here, a known reflector is used as the reference reflector for interferometric least-squares migration, and the data are approximately redatumed to this reference reflector before imaging. This virtual redatuming mitigates the repeatability errors in the time-lapse migration image. Results with synthetic and field data show that interferometric least-squares migration can sometimes reduce or eliminate artifacts caused by non-repeatability in time-lapse surveys and provide a high-resolution estimate of the time-lapse change in the reservoir.

We present an integrated interpretation case study of pre-stack depth migration and diffraction imaging in two Dutch North Sea gas fields. Diffraction imaging, as the detector of discontinuities at very high resolution and unlimited by illumination constraints, is the ideal technique for mapping gas accumulations at fault cuts (DI as DHI). The diffraction image, being a migrated physical wavefield, has amplitude, frequency, phase, polarity and tuning properties which can all be used to enhance its interpretation value. We use the diffraction imaging response of elementary models to build up an edge diffraction calculus and thus model and predict responses from more complex structures. This confirms the details seen in the diffraction images and well data from the studied gas fields. Diffraction imaging allows for a significant refinement of the interpretation resulting in more accurate definition of drilling targets and lower uncertainty in resource volumes.

Autonomous marine vehicles instrumented with seismic sensors allow for new efficient seismic survey designs. One such design is the swarm survey, where a group, or swarm, of slow moving autonomous marine vehicles record seismic data from shots fired by a source vessel sailing around circles within the swarm. The size of the swarm is dictated by the maximum offset requirement of the survey, and it can be shaped to acquire wide- and full-azimuth data. The swarm survey design equation describes the relationship between the source and receiver positions of the survey and the subsurface coverage or fold. It is used to adapt the swarm to the seismic survey requirements and to calculate survey duration time estimates as function of available equipment. It is shown that a survey conducted by a slowly moving swarm requires six times fewer shots than an equivalent seabed node survey conducted over 85.5 km2. Swarm surveys can also be adapted to efficiently conduct infill surveys and replace multi-vessel undershoots. The efficiency of the survey can further be increased when the autonomous marine vehicles are towing short streamers with multiple receivers. Synthetic tests show that the seismic images for swarm surveys are comparable to those from streamer surveys, while little variation in image quality is found when reducing the number of autonomous marine vehicles but equipping them with a short streamer with multiple receivers.

Selecting a seismic time-to-depth conversion method can be a subjective choice that is made by geophysicists, and is particularly difficult if the accuracy of these methods is unknown. This study presents an automated statistical approach for assessing seismic time-to-depth conversion accuracy by integrating the cross-validation method with four commonly used seismic time-to-depth conversion methods. To showcase this automated approach, we use a regional dataset from the Cooper and Eromanga basins, Australia, consisting of 13 three-dimensional (3D) seismic surveys, 73 two-way-time surface grids and 729 wells. Approximately 10,000 error values (predicted depth vs. measured well depth) and associated variables were calculated. The average velocity method was the most accurate overall (7.6 m mean error); however, the most accurate method and the expected error changed by several metres depending on the combination and value of the most significant variables. Cluster analysis tested the significance of the associated variables to find that the seismic survey location (potentially related to local geology (i.e. sedimentology, structural geology, cementation, pore pressure, etc.), processing workflow, or seismic vintage), formation (potentially associated with reduced signal-to-noise with increasing depth or the changes in lithology), distance to the nearest well control, and the spatial location of the predicted well relative to the existing well data envelope had the largest impact on accuracy. Importantly, the effect of these significant variables on accuracy were found to be more important than choosing between the four methods, highlighting the importance of better understanding seismic time-to-depth conversions, which can be achieved by applying this automated cross-validation method.

Porosity measurement is an important step for petrophysical characterization of reservoir rocks, as porosity is essential for analysing elastic properties and estimating the capacity of rocks to hold hydrocarbon resources. Commonly used porosity measurement methods fail to work on heavy oil sands, because of the loose fragile sand frame and solid-like irreducible heavy oil. We develop three methods to measure the porosity of heavy oil sands, which are feasible and affordable in most laboratories. Method 1 involves calculating the bulk volume of the sample by measuring its physical dimensions directly. Method 2 uses calibrated sample weight and volume (after removing the protecting foil cover and metal clips).Method 3 first applies pressurizing on samples and then measures the weight and volume of the bare samples. The measurement results of the three methods are then compared and method 3 is determined as the most reliable, which is also verified by the porosity log. Finally, an analysis of the potential sources of errors associated with method 3 is performed.

Modelling unconventional reservoirs requires increasingly complex physics to describe the phenomena that affect the performance and efficiency of horizontal wells. For example, poroelastic geomechanical simulation (Ouenes et al., 2017b) is needed to model frac hits and well interferences resulting from the presence of stress and pressure dependent natural fractures and other geologic factors that see their permeability increase during stimulation. Recent field observations related to stress relaxation required the introduction of viscoelasticity (Peterson et al., 2018) to better understand the effect of timing during fracing. Lastly, the importance of interfaces and their impact on fracture height growth required the introduction of 3D damage mechanics (Aimene et al., 2018) to model the propagation of hydraulic fractures in a more realistic rock volume that considers the layering of the various lithologies and the resulting weak interfaces that will in turn interact with hydraulic fractures. This increasing complexity in physics is also combined with the need to provide solutions very quickly, if not in real time As the physics of unconventional reservoirs becomes more complex, the data available at each well to correctly model that physics is dwindling at an alarming rate. The introduction of the continuum multiscale approach (Ouenes et al., 2017b) and the use of surface drilling data provide the unique opportunity to address both the lack of data and the increasingly complex physics. In the absence of wireline logs and seismic data, surface drilling data collected at each well is used at different scales ranging from wellbore to reservoir scale. In this process called ‘Inverse Design and Validation’, the information contained in the surface drilling data is used 1) during the drilling to optimize the landing zone and geosteering, 2) during the design of the completion to geoengineer the stages to account for the variability of the rock, and 3) to build 3D models that will allow the correct estimation of petrophysical, geomechanical properties and stresses needed in 3D planar frac simulators as well as fluid flow simulation. These various applications are examined in the next sections.

Accurate modelling of the conductivity structure of mineralisations can often be difficult. In order to remedy this, a parametric approach is often used. We have developed a parametric thin-sheet code, with a variable overburden. The code is capable of performing inversions of time-domain airborne electromagnetic data, and it has been tested successfully on both synthetic data and field data. The code implements an integral solution containing one or more conductive sheets, buried in a half-space with a laterally varying conductive overburden. This implementation increases the area of applicability compared to, for example, codes operating in free space, but it comes with a significant increase in computational cost. To minimise the cost, the code is parallelised using OpenMP and heavily optimised, which means that inversions of field data can be performed in hours on multiprocessor desktop computers. The code models the full system transfer function of the electromagnetic system, including variable flight height. The code is demonstrated with a synthetic example imitating a mineralisation buried underneath a conductive meadow. As a field example, the Valen mineral deposit, which is a graphite mineral deposit located in a variable overburden, is successfully inverted. Our results match well with previous models of the deposit; however, our predicted sheet remains inconclusive. These examples collectively demonstrate the effectiveness of our thin-sheet code.

The theory and practice of multisource full waveform inversion of marine supergathers are described with a frequency-selection strategy. The key enabling property of frequency selection is that it eliminates the crosstalk among sources, thus overcoming the aperture mismatch of marine multisource inversion. Tests on multisource full waveform inversion of synthetic marine data and Gulf of Mexico data show speedups of 4× and 8×, respectively, compared to conventional full waveform inversion. This article is protected by copyright. All rights reserved

Numerous examples of reservoir fields from continental and marine environments involve thin-bedded geology, yet, the inter-relationship between thin-bedded geology, fluid flow and seismic wave propagation is poorly understood. In this paper, we explore the 4D seismic signature due to saturation changes of gas within thin layers, and address the challenge of identifying the relevant scales and properties, which correctly define the geology, fluid flow and seismic wave propagation in the field. Based on the study of an outcrop analogue for a thin-bedded turbidite, we model the time-lapse seismic response to fluid saturation changes for different levels of model scale, and explore discrepancies in quantitative seismic attributes caused by upscaling. Our model reflects the geological complexity associated with thin-bedded turbidites, and its coupling to fluid flow, which in turn affects the gas saturation distribution in space, and its time-lapse seismic imprint. Rock matrix and fluid properties are modelled after selected fields to reproduce representative field models with realistic impedance contrasts. In addition, seismic modelling includes multiples, in order to assess their contribution in seismic propagation through thin gas layers. Our results show that multiples could contribute significantly to the measured amplitudes in the case of thin-bedded geology. This suggests that forward/inverse modelling involving the flow simulation and seismic domains used in time-lapse seismic interpretation should account for thin layers, when these are present in the geological setting.

All seismic data, whether 2D, 3D, post-stack or pre-stack, contains noise. Typically, this noise is comprised of both coherent and random components. Coherent noise presents itself as regular patterns in the seismic data. It may appear to be random or coherent depending on the orientation of the slice on which it is being observed. For example, coherent noise associated with acquisition may appear random on vertical slices through the volume, with its coherent nature becoming apparent on horizontal slices through the volume. When seismic data is processed, an effort is made to reduce the coherent noise in the seismic data by applying a variety of signal processing techniques. However, when the seismic volume is delivered to the client, it often includes remnant noise that processing was unable to remove without having a deleterious effect on the amplitudes and bandwidth of the seismic data. Since the processed seismic volume typically contains coherent noise, managing that noise within an interpretation system is critical, as it has a significant negative impact on semi-automatic and automatic interpretation workflows and techniques including autotracking of horizons, imaging of faults and fractures, automatic extraction of faults, and interpretation of stratigraphy and geomorphology. An obvious example is the effect of noise on edge attributes (i.e., ‘coherence’ class attributes). Any noise in the seismic data, whether random or coherent, will appear as edges in the seismic attribute volume and may obscure the geologic features of interest in the edge attribute volume (faults, fractures, stratigraphy, and geomorphology). Finally, many interpreters today must use older 3D seismic volumes, merged seismic volumes of a variety of acquisition designs and processing workflows. Even if the pre-stack data is still available, their company may not be in a position to spend the money required to re-process the data. Yet they still need and expect to be able to use modern advanced interpretation technology on the data. In response to this need a post-stack structurally oriented coherent noise filtering process has been developed and is described, with an application to 3D seismic surveys from the North Sea. The results are evaluated by comparing seismic volumes, edge attribute volumes, and amplitude and phase spectra pre- and post-filtering.

Frequency Decomposition (FD) colour blending of 3D seismic data has become a mainstream technique used by oil and gas industry G&G specialists for imaging subsurface geology. The workflow involves creating frequency band-restricted components of the seismic data and blending these together into a single volume, typically using a three-dimensional, red-green-blue (RGB) colour scheme. The blends often produce high-resolution, detailed images capable of detecting very subtle features owing to the interference between three frequency band components which tune at different frequencies. A major advantage is being able to assess distribution and extrapolation of results away from well locations since the results are volumetric and not restricted to a well location. The workflow has typically been applied in a qualitative manner to identify depositional features, structures and geomorphologies visually based on colour changes in the blends. However, the link between the colours and rock physics is poorly understood.

In this paper, we propose a novel three-dimensional receiver deghosting algorithm that is capable of deghosting both horizontal and slanted streamer data in a theoretically consistent manner. Our algorithm honours wave propagation phenomena in a true three-dimensional sense and frames the three-dimensional receiver deghosting problem as a Lasso problem. The ultimate goal is to minimise the mismatch between the actual measurements and the simulated wavefield with an L1 constraint applied in the extended Radon space to handle the underdetermined nature of this problem.We successfully demonstrate our algorithm on a modified three-dimensional EAGE/SEG Overthrust model and a Red Sea marine dataset.

High-resolution reflection seismics is a powerful tool that can provide the required resolution for subsurface imaging and monitoring in urban settings. Shallow seismic reflection data acquired in soil-covered sites are often contaminated by source-coherent surface waves and other linear moveout noises (LMON) that might be caused by, e.g., anthropogenic sources or harmonic distortion in vibroseis data. In the case of shear-wave seismic reflection data, such noises are particularly problematic as they overlap the useful shallow reflections. We have developed new schemes for suppressing such surface-wave noise and LMON while still preserving shallow reflections, which are of great interest to high-resolution near-surface imaging. We do this by making use of two techniques. First, we make use of seismic interferometry to retrieve predominantly source-coherent surface waves and LMON. We then adaptively subtract these dominant source-coherent surface waves and LMON from the seismic data in a separate step. We illustrate our proposed method using synthetic and field data. We compare results from our method with results from frequency–wave-number (f-k) filtering. Using synthetic data, we show that our schemes are robust in separating shallow reflections from source-coherent surface waves and LMON even when they share very similar velocity and frequency contents, whereas f-k filtering might cause undesirable artefacts. Using a field shear-wave reflection dataset characterised by overwhelming LMON, we show that the reflectors at a very shallow depth can be imaged because of significant suppression of the LMON due to the application of the scheme that we have developed.

Real-time microseismic detection at offshore hydrocarbon fields is on its way to becoming a standard monitoring tool. Recently, increased focus on injection and overburden surveillance for an improved health, safety and environment (HSE) and cost saving has led to this development. Several hydrocarbon fields are already equipped with permanent reservoir monitoring (PRM) systems with seismic sensors permanently installed at the seafloor (Caldwell et al., 2015), and similar installations are planned or under consideration for some other offshore fields. PRM systems are in principle designed for acquiring active time-lapse seismic data 1-2 times per years, and as such, they are not used during most of their lifetime. But apart from active seismic, PRM systems can also be used for recording passive seismic data. With appropriate processing and analysis methods, such as microseismic event detection, the continuous stream of passive data can be converted into useful real-time subsurface information. This results in improved HSE, and therefore a more valuable PRM system. In 2014, a mini-PRM system with 172 multi-component sensors was installed at the Oseberg field, offshore Norway. The mini-PRM system indeed demonstrated the feasibility of injection and overburden surveillance using real-time passive seismic (Bussat et al., 2016). Despite high installation costs, a cost/benefit evaluation shows net benefits for the Oseberg system owing to better control on waste injection rates. The next step, and topic of the current paper, is to scale up and transfer the learnings from the small Oseberg system to the large Grane PRM system, so as to enable processing and analysis of large amounts of passive data and allow for real-time injection monitoring at Grane. Compared to the Oseberg case, the microseismic data processing is distributed and optimized to be able to use many more sensors and monitor larger subsurface volumes with increased resolution. Moreover, the detection method is improved from an originally strict semblance-based method to also include signal-to-noise (S/N) analysis of the semblance-weighted stack. Crucial noise filtering is integrated into the real-time processing flow, enhancing the sensitivity of the system and ensuring the best possible detection/localization at any time. Key personnel receive an alert immediately after an event detection. This makes the monitoring fully integrated into the follow-up of the daily operation.

There is an increasing demand for trustworthy engineering geological conceptual models in urban areas due to an increasing trend in the underground infrastructure construction. Good-quality site investigations can reduce the risk of encountering unexpected geological conditions during construction. Geoelectrical measurements can be used as a tool for providing an overview of the site conditions and serve as a base for planning a geotechnical drilling program and for integration of the results. Geophysical surveys in urban environments may encounter problems due to strict logistical constraints and may be severely affected by electric and electromagnetic noise. Careful processing of the data is necessary to obtain a reliable estimation of the electrical properties of the ground, both electrical resistivity and chargeability. A large three-dimensional dataset was acquired in the suburban area of Stockholm (Sweden), with the aim of investigating a weak zone in the crystalline bedrock, which had been pointed out by prior geological and geotechnical surveys. Full waveforms of potential dipoles were recorded and processed for removing harmonic noise and background drift. Moreover, a statistical algorithm for handling the quality of the full-waveform shapes has been proposed. The goodness-of-fit test identifies full waveforms with noise that derives from direct current injections, caused by grounding spots of the adjacent metro line. The processed dataset is inverted for electrical resistivity and integral chargeability. The results image a large three-dimensional volume of the underground. The inverted distribution of geophysical quantities marks out the presence of a wide zone of weak rock, which was not identified by geotechnical probing in the site investigation but documented during the construction phase. Such zones can potentially cause severe problems during the construction of underground infrastructure.